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Biosensors and Smart Analytical Systems in Food Quality and Safety:...
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Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Quality and Safety".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 28915

Special Issue Editors

Dr. Jordi Riu

E-Mail Website
Guest Editor
Department of Analytical and Organic Chemistry, Universitat Rovira i Virgili, Marcel·li Domingo 1, 43007-Tarragona, Spain
Interests: biosensors; electrochemistry; spectroscopy; chemometrics; smart analytical systems; portable instrumentation
Prof. Dr. Barbara Giussani

E-Mail Website
Guest Editor
Department of Science and High Technology, University of Insubria, Via Valleggio, 11, 22100 Como, Italy
Interests: control process strategies through multivariate analysis; design and development of smart analytical strategies to solve real-world problems, from sampling to data analysis; Infrared and near-infrared spectroscopies; especially using portable sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Foodborne diseases are currently a serious concern that affect 600 million people worldwide. They are responsible for over 9.4 million illnesses every year in the USA, and a total of 5079 foodborne outbreaks were reported in 2017 in the European Union. The demand for developing accurate, simple, rapid, low-cost and ideally portable analytical systems that can make point-of-care analyses is constantly growing. We can safely say that food quality and safety are the main targets of investigation in food production.

Biosensors are an alternative to conventional methods, and their way of functioning also takes most of the advantages of green chemistry. They are generally compact, which makes them prone to miniaturize and they are easily integrated with standard electronic microfabrication which makes it possible for devices to be wearable and be used for multiplex sensing, requiring low volumes of sample and reagents. Similarly to biosensors, smart analytical systems that use miniaturized spectrometric instrumentation have made significant advances in the last years, offering nowadays significant advantages in terms of mobility, price, size or weight.

Apart from meeting most of the requisites of green chemistry, one of the main advantages of biosensors and smart analytical systems is their portability, what makes them ideal tools in the monitoring and control of food quality and safety, for instance in foodborne outbreaks where a rapid detection in situ is required to control the emergence.

This Special Issue is a great opportunity for colleagues working with biosensors and smart analytical systems assessing the quality or safety in foods. Submission of original research articles and reviews are encouraged.

Dr. Jordi Riu
Prof. Dr. Barbara Giussani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biosensors
  • spectrometry
  • smart analytical systems
  • portable instrumentation
  • food quality
  • food security
  • chemometrics

Published Papers (16 papers)

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Editorial

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4 pages, 187 KiB  
Editorial
Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives
by Barbara Giussani and Jordi Riu
Foods 2023, 12(12), 2292; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12122292 - 07 Jun 2023
Cited by 1 | Viewed by 852
Abstract
The primary focus of research in food production revolves around ensuring food quality and safety [...] Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)

Research

Jump to: Editorial, Review

14 pages, 4549 KiB  
Article
Capillary-Assisted Monitoring of Milk Freshness via a Porous Cellulose-Based Label with High pH Sensitivity
by Ruoting Liu, Wenrui Chi, Qihao Zhu, Hailan Jin, Jian Li and Lijuan Wang
Foods 2023, 12(9), 1857; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12091857 - 29 Apr 2023
Cited by 2 | Viewed by 1137
Abstract
A cellulose-based matrix for monitoring milk freshness (MF) was produced from rice straw particles (RSPs) in a 0.125–0.150 mm that was bis-quaternized to attach bromocresol purple (BP) as a sensor. Under alkali conditions, the obstinate structure of the rice straw had opened, thereby [...] Read more.
A cellulose-based matrix for monitoring milk freshness (MF) was produced from rice straw particles (RSPs) in a 0.125–0.150 mm that was bis-quaternized to attach bromocresol purple (BP) as a sensor. Under alkali conditions, the obstinate structure of the rice straw had opened, thereby improving the accessibility of the cellulose. Bis-quaternization created more adsorption sites for BP. The maximum adsorption capacity was 97.68 mg/g. The sensors were interwoven with cellulosic fibers to form the cellulose-based label with a relatively loose three-dimensional structure via hydrogen bonds. As the proportion of BP-BCRPs was increased from 10% to 40%, the air permeability of the label increased from 3.76 to 15.01 mm/s, which increased the response to the tested gases (10.12 s for 1 mL of acetic acid). The intelligent label exhibited excellent sensitivity at pH values of 3–9 with highly saturated color changes. During the storage period, the label color shifted from blue-purple to yellow as acidity was increased from 17.24 to 19.8 °T due to capillarity action, providing a timely warning to consumers. The prepared colorimetric porous intelligent cellulose-based label is suitable for monitoring of MF. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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13 pages, 2638 KiB  
Article
A Feasibility Study towards the On-Line Quality Assessment of Pesto Sauce Production by NIR and Chemometrics
by Daniele Tanzilli, Alessandro D’Alessandro, Samuele Tamelli, Caterina Durante, Marina Cocchi and Lorenzo Strani
Foods 2023, 12(8), 1679; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12081679 - 18 Apr 2023
Cited by 2 | Viewed by 1317
Abstract
The food industry needs tools to improve the efficiency of their production processes by minimizing waste, detecting timely potential process issues, as well as reducing the efforts and workforce devoted to laboratory analysis while, at the same time, maintaining high-quality standards of products. [...] Read more.
The food industry needs tools to improve the efficiency of their production processes by minimizing waste, detecting timely potential process issues, as well as reducing the efforts and workforce devoted to laboratory analysis while, at the same time, maintaining high-quality standards of products. This can be achieved by developing on-line monitoring systems and models. The present work presents a feasibility study toward establishing the on-line monitoring of a pesto sauce production process by means of NIR spectroscopy and chemometric tools. The spectra of an intermediate product were acquired on-line and continuously by a NIR probe installed directly on the process line. Principal Component Analysis (PCA) was used both to perform an exploratory data analysis and to build Multivariate Statistical Process Control (MSPC) charts. Moreover, Partial Least Squares (PLS) regression was employed to compute real time prediction models for two different pesto quality parameters, namely, consistency and total lipids content. PCA highlighted some differences related to the origin of basil plants, the main pesto ingredient, such as plant age and supplier. MSPC charts were able to detect production stops/restarts. Finally, it was possible to obtain a rough estimation of the quality of some properties in the early production stage through PLS. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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16 pages, 3963 KiB  
Article
On the Importance of Investigating Data Structure in Miniaturized NIR Spectroscopy Measurements of Food: The Case Study of Sugar
by Giulia Gorla, Paolo Taborelli, Cristina Alamprese, Silvia Grassi and Barbara Giussani
Foods 2023, 12(3), 493; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12030493 - 20 Jan 2023
Cited by 5 | Viewed by 1514
Abstract
Alongside the increasing proofs of efficacy of miniaturized NIR instruments in food-related scenarios, it is progressively growing the number of end-users, even incentivized by the low-cost of the sensors. While attention is paid to the analytical protocol–from sampling to data collection, up to [...] Read more.
Alongside the increasing proofs of efficacy of miniaturized NIR instruments in food-related scenarios, it is progressively growing the number of end-users, even incentivized by the low-cost of the sensors. While attention is paid to the analytical protocol–from sampling to data collection, up to the data processing, the importance of error investigation in raw data is generally underestimated. Understanding the sources and the structure of uncertainty related to the raw data improves the quality of measurements and suggests the correct planning of the experiments, as well as helps in chemometric model development. The goal of chemometric modeling is to separate information from noise; therefore, a description of the nature of measurement error structure is necessary. Among the different approaches, we present the study of the Error Covariance Matrices (ECMs) and their decomposition in a bilinear structure as a powerful method to study the main sources of variability when using miniaturized NIR sensors in the actual way of use. Granulated and lump sugar samples were chosen as the case study and analyzed with two miniaturized spectrometers working in the NIR regions around 1350–2550 nm and 900–1750 nm, respectively, in dispersive reflectance mode. Results show that having some insights on multivariate measurement errors associated with spectra could be interesting in paving the way for several applications. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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12 pages, 1262 KiB  
Article
Characterizing Spray-Dried Powders through NIR Spectroscopy: Effect of Two Preparation Strategies for Calibration Samples and Comparison of Two Types of NIR Spectrometers
by Zhiyang (Stan) Tu, Joseph Irudayaraj and Youngsoo Lee
Foods 2023, 12(3), 467; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12030467 - 19 Jan 2023
Cited by 2 | Viewed by 1748
Abstract
Emerging portable near infrared (NIR) spectroscopic approaches coupled with data analysis and chemometric techniques provide opportunities for the rapid characterization of spray-dried products and process optimization. This study aimed to enhance the understanding of applying NIR spectroscopy in spray-dried samples by comparing two [...] Read more.
Emerging portable near infrared (NIR) spectroscopic approaches coupled with data analysis and chemometric techniques provide opportunities for the rapid characterization of spray-dried products and process optimization. This study aimed to enhance the understanding of applying NIR spectroscopy in spray-dried samples by comparing two sample preparation strategies and two spectrometers. Two sets of whey protein–maltodextrin matrixes, one with a protein content gradient and one with a consistent protein content, were spray-dried, and the effect of the two preparation strategies on NIR calibration model development was studied. Secondly, a portable NIR spectrometer (PEAK) was compared with a benchtop NIR spectrometer (CARY) for the moisture analysis of prepared samples. When validating models with the samples with focused protein contents, the best PLS protein models established from the two sample sets had similar performances. When comparing two spectrometers, although CARY outperformed PEAK, PEAK still demonstrated reliable performance for moisture analysis, indicating that it is capable as an inline sensor. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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16 pages, 3740 KiB  
Article
Identification of Illicit Conservation Treatments in Fresh Fish by Micro-Raman Spectroscopy and Chemometric Methods
by Elisa Robotti, Masho Hilawie Belay, Elisa Calà, Alessandro Benedetto, Simone Cerruti, Marzia Pezzolato, Francesco Pennisi, Maria Cesarina Abete, Emilio Marengo and Paola Brizio
Foods 2023, 12(3), 449; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12030449 - 18 Jan 2023
Cited by 4 | Viewed by 1531
Abstract
In the field of food control for fresh products, the identification of foods subjected to illicit conservation treatments to extend their shelf life is fundamental. Fresh fish products are particularly subjected to this type of fraud due to their high commercial value and [...] Read more.
In the field of food control for fresh products, the identification of foods subjected to illicit conservation treatments to extend their shelf life is fundamental. Fresh fish products are particularly subjected to this type of fraud due to their high commercial value and the fact that they often have to be transported over a long distance, keeping their organoleptic characteristics unaltered. Treatments of this type involve, e.g., the bleaching of the meat and/or the momentary abatement of the microbial load, while the degradation process continues. It is therefore important to find rapid methods that allow the identification of illicit treatments. The study presented here was performed on 24 sea bass samples divided into four groups: 12 controls (stored on ice in the fridge for 3 or 24 h), and 12 treated with a Cafodos-like solution for 3 or 24 h. Muscle and skin samples were then characterized using micro-Raman spectroscopy. The data were pre-processed by smoothing and taking the first derivative and then PLS-DA models were built to identify short- and long- term effects on the fish’s muscle and skin. All the models provided the perfect classification of the samples both in fitting and cross-validation and an analysis of the bands responsible for the effects was also reported. To the best of the authors’ knowledge, this is the first time Raman spectroscopy has been applied for the identification of a Cafodos-like illicit treatment, focusing on both fish muscle and skin evaluation. The procedure could pave the way for a future application directly on the market through the use of a portable device. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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14 pages, 2152 KiB  
Article
Variation and Correlation Analysis of Flavour and Bacterial Diversity of Low-Salt Hotpot Sauce during Storage
by Yanan Xia, Bayaer Eerdun, Junlin Wang, Yankai Li, Quan Shuang and Yongfu Chen
Foods 2023, 12(2), 333; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12020333 - 10 Jan 2023
Cited by 2 | Viewed by 1313
Abstract
Culinary circles have experienced a recent trend towards low-salt hotpot sauces. Here, changes in the physicochemical quality, flavour, and bacterial diversity of hotpot sauces with different salt concentrations were studied during storage. The results indicated that the peroxide and acid values of hotpot [...] Read more.
Culinary circles have experienced a recent trend towards low-salt hotpot sauces. Here, changes in the physicochemical quality, flavour, and bacterial diversity of hotpot sauces with different salt concentrations were studied during storage. The results indicated that the peroxide and acid values of hotpot sauce increased gradually and that the quality began to deteriorate with storage. A storage temperature of 4 °C and salt concentration above 4.4% significantly reduced spoilage. The salt concentration had no significant effect on the flavour but extended storage resulted in significant differences in flavour reflected in the changes of sweet, sour, bitter, umami, aftertaste-A, abundance, organic sulphide, and alkanes. Significant differences were found in the bacterial composition between samples stored at different temperatures. Norank-f-o-Chloroplast was the main bacterium in the samples stored at low temperatures, which was beneficial for preservation. Bacillus was detected in 4.1% NaCl samples stored at 25 °C, directly promoting sauce spoilage and an unpleasant flavour. This bacterium signalled the spoilage of low-salt hotpot sauce stored at room temperature. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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17 pages, 965 KiB  
Article
Feature Reduction for the Classification of Bruise Damage to Apple Fruit Using a Contactless FT-NIR Spectroscopy with Machine Learning
by Jean Frederic Isingizwe Nturambirwe, Eslam A. Hussein, Mattia Vaccari, Christopher Thron, Willem Jacobus Perold and Umezuruike Linus Opara
Foods 2023, 12(1), 210; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12010210 - 03 Jan 2023
Cited by 13 | Viewed by 3289
Abstract
Spectroscopy data are useful for modelling biological systems such as predicting quality parameters of horticultural products. However, using the wide spectrum of wavelengths is not practical in a production setting. Such data are of high dimensional nature and they tend to result in [...] Read more.
Spectroscopy data are useful for modelling biological systems such as predicting quality parameters of horticultural products. However, using the wide spectrum of wavelengths is not practical in a production setting. Such data are of high dimensional nature and they tend to result in complex models that are not easily understood. Furthermore, collinearity between different wavelengths dictates that some of the data variables are redundant and may even contribute noise. The use of variable selection methods is one efficient way to obtain an optimal model, andthis was the aim of this work. Taking advantage of a non-contact spectrometer, near infrared spectral data in the range of 800–2500 nm were used to classify bruise damage in three apple cultivars, namely ‘Golden Delicious’, ‘Granny Smith’ and ‘Royal Gala’. Six prominent machine learning classification algorithms were employed, and two variable selection methods were used to determine the most relevant wavelengths for the problem of distinguishing between bruised and non-bruised fruit. The selected wavelengths clustered around 900 nm, 1300 nm, 1500 nm and 1900 nm. The best results were achieved using linear regression and support vector machine based on up to 40 wavelengths: these methods reached precision values in the range of 0.79–0.86, which were all comparable (within error bars) to a classifier based on the entire range of frequencies. The results also provided an open-source based framework that is useful towards the development of multi-spectral applications such as rapid grading of apples based on mechanical damage, and it can also be emulated and applied for other types of defects on fresh produce. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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11 pages, 1674 KiB  
Article
Lipids in a Nutshell: Quick Determination of Lipid Content in Hazelnuts with NIR Spectroscopy
by Elena Cazzaniga, Nicola Cavallini, Alessandro Giraudo, Gentian Gavoci, Francesco Geobaldo, Mattia Pariani, Daniela Ghirardello, Giuseppe Zeppa and Francesco Savorani
Foods 2023, 12(1), 34; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12010034 - 22 Dec 2022
Cited by 1 | Viewed by 1708
Abstract
Hazelnuts (Corylus avellana L.) are among the most consumed dry fruits all over the world. Their commercial quality is defined, above all, by origin and dimension, as well as by lipid content. Evaluation of this parameter is currently performed with chemical methods, [...] Read more.
Hazelnuts (Corylus avellana L.) are among the most consumed dry fruits all over the world. Their commercial quality is defined, above all, by origin and dimension, as well as by lipid content. Evaluation of this parameter is currently performed with chemical methods, which are expensive, time consuming, and complex. In the present work, the near-infrared (NIR) spectroscopy, using both a benchtop research spectrometer and a retail handheld instrument, was evaluated in comparison with the traditional chemical approach. The lipid content of hazelnuts from different growing regions of origin (Italy, Chile, Turkey, Georgia, and Azerbaijan) was determined with two NIR instruments: a benchtop FT-NIR spectrometer (Multi Purpose Analyser—MPA, by Bruker), equipped with an integrating sphere and an optic fibre probe, and the pocket-sized, battery-powered SCiO molecular sensor (by Consumer Physics). The Randall/Soxtec method was used as the reference measurement of total lipid content. The collected NIR spectra were inspected through multivariate data analysis. First, a Principal Component Analysis (PCA) model was built to explore the information contained in the spectral datasets. Then, a Partial Least Square (PLS) regression model was developed to predict the percentage of lipid content. PCA showed samples distributions that could be linked to their total crude fat content determined with the Randall/Soxtec method, confirming that a trend related to the lipid content could be detected in the spectral data, based on their chemical profiles. PLS models performed better with the MPA instrument than SCiO, with the highest R2 of prediction (R2PRED = 0.897) achieved by MPA probe, while this parameter for SCiO was much lower (R2PRED = 0.550). Further analyses are necessary to evaluate if more acquisitions may lead to better performances when using the SCiO portable spectrometer. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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11 pages, 8820 KiB  
Article
Coupled Gold Nanoparticles with Aptamers Colorimetry for Detection of Amoxicillin in Human Breast Milk Based on Image Preprocessing and BP-ANN
by Ziqian Ye, Jinglong Du, Keyu Li, Zhilun Zhang, Peng Xiao, Taocui Yan, Baoru Han and Guowei Zuo
Foods 2022, 11(24), 4101; https://0-doi-org.brum.beds.ac.uk/10.3390/foods11244101 - 19 Dec 2022
Cited by 3 | Viewed by 1465
Abstract
Antibiotic residues in breast milk can have an impact on the intestinal flora and health of babies. Amoxicillin, as one of the most used antibiotics, affects the abundance of some intestinal bacteria. In this study, we developed a convenient and rapid process that [...] Read more.
Antibiotic residues in breast milk can have an impact on the intestinal flora and health of babies. Amoxicillin, as one of the most used antibiotics, affects the abundance of some intestinal bacteria. In this study, we developed a convenient and rapid process that used a combination of colorimetric methods and artificial intelligence image preprocessing, and back propagation-artificial neural network (BP-ANN) analysis to detect amoxicillin in breast milk. The colorimetric method derived from the reaction of gold nanoparticles (AuNPs) was coupled to aptamers (ssDNA) with different concentrations of amoxicillin to produce different color results. The color image was captured by a portable image acquisition device, and image preprocessing was implemented in three steps: segmentation, filtering, and cropping. We decided on a range of detection from 0 µM to 3.9 µM based on the physiological concentration of amoxicillin in breast milk and the detection effect. The segmentation and filtering steps were conducted by Hough circle detection and Gaussian filtering, respectively. The segmented results were analyzed by linear regression and BP-ANN, and good linear correlations between the colorimetric image value and concentration of target amoxicillin were obtained. The R2 and MSE of the training set were 0.9551 and 0.0696, respectively, and those of the test set were 0.9276 and 0.1142, respectively. In prepared breast milk sample detection, the recoveries were 111.00%, 98.00%, and 100.20%, and RSDs were 6.42%, 4.27%, and 1.11%. The result suggests that the colorimetric process combined with artificial intelligence image preprocessing and BP-ANN provides an accurate, rapid, and convenient way to achieve the detection of amoxicillin in breast milk. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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12 pages, 1096 KiB  
Article
Solvent-Free Lipid Separation and Attenuated Total Reflectance Infrared Spectroscopy for Fast and Green Fatty Acid Profiling of Human Milk
by Christopher Karim Akhgar, Victoria Ramos-Garcia, Vanessa Nürnberger, Alba Moreno-Giménez, Julia Kuligowski, Erwin Rosenberg, Andreas Schwaighofer and Bernhard Lendl
Foods 2022, 11(23), 3906; https://0-doi-org.brum.beds.ac.uk/10.3390/foods11233906 - 03 Dec 2022
Cited by 2 | Viewed by 1369
Abstract
This study presents the first mid-infrared (IR)-based method capable of simultaneously predicting concentrations of individual fatty acids (FAs) and relevant sum parameters in human milk (HM). Representative fat fractions of 50 HM samples were obtained by rapid, two-step centrifugation and subsequently measured with [...] Read more.
This study presents the first mid-infrared (IR)-based method capable of simultaneously predicting concentrations of individual fatty acids (FAs) and relevant sum parameters in human milk (HM). Representative fat fractions of 50 HM samples were obtained by rapid, two-step centrifugation and subsequently measured with attenuated total reflection IR spectroscopy. Partial least squares models were compiled for the acquired IR spectra with gas chromatography-mass spectrometry (GC-MS) reference data. External validation showed good results particularly for the most important FA sum parameters and the following individual FAs: C12:0 (R2P = 0.96), C16:0 (R2P = 0.88), C18:1cis (R2P = 0.92), and C18:2cis (R2P = 0.92). Based on the obtained results, the effect of different clinical parameters on the HM FA profile was investigated, indicating a change of certain sum parameters over the course of lactation. Finally, assessment of the method’s greenness revealed clear superiority compared to GC-MS methods. The reported method thus represents a high-throughput, green alternative to resource-intensive established techniques. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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12 pages, 4323 KiB  
Article
Development of a Reliable ic-ELISA with a Robust Antimatrix Interference Capability Based on QuEChERS Technology for the Rapid Detection of Zearalenone in Edible and Medical Coix Seeds and Subsequent Risk Assessments
by Kaiyi Guan, Rentang Huang, Hongmei Liu, Yuxin Huang, Ali Chen, Xiangsheng Zhao, Shumei Wang and Lei Zhang
Foods 2022, 11(19), 2983; https://0-doi-org.brum.beds.ac.uk/10.3390/foods11192983 - 24 Sep 2022
Cited by 6 | Viewed by 1480
Abstract
Indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) is an ideal immunoassay method for large-scale screenings to detect mycotoxin contaminants. However, the matrix effect of complicated samples has always been challenging when performing immunoassays, as it leads to false-positive or negative results. In this study, [...] Read more.
Indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) is an ideal immunoassay method for large-scale screenings to detect mycotoxin contaminants. However, the matrix effect of complicated samples has always been challenging when performing immunoassays, as it leads to false-positive or negative results. In this study, convenient QuEChERS technology combined with optimizing the dilution solvent was ingeniously used to eliminate interference from the sample matrix to greatly improve the detection accuracy, and reliable ic-ELISAs for the two official tolerance levels of 60 and 500 μg/kg were developed to screen zearalenone (ZEN) in edible and medical coix seeds without any further correction. Then, the 122 batches of coix seeds were determined, and the positive rate was up to 97.54%. The contaminated distribution was further analyzed, and risk assessment was subsequently performed for its edible and medical purposes. The findings indicated that consumption of coix seeds with higher ZEN contamination levels may cause adverse health effects for both medical and edible consumption in the adult population; even under the condition of average contamination level, ZEN from coix seeds was the more prominent contributor to the total risk compared to other sources when used as food; thus, effective prevention and control should be an essential topic in the future. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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13 pages, 2212 KiB  
Article
A Comparative Study of Benchtop and Portable NIR and Raman Spectroscopic Methods for the Quantitative Determination of Curcuminoids in Turmeric Powder
by Putthiporn Khongkaew, Jordi Cruz, Judit Puig Bertotto, Vanessa Cárdenas, Manel Alcalà, Nantana Nuchtavorn and Chutima Phechkrajang
Foods 2022, 11(15), 2187; https://0-doi-org.brum.beds.ac.uk/10.3390/foods11152187 - 22 Jul 2022
Cited by 4 | Viewed by 2312
Abstract
Turmeric consumption is continually increasing worldwide. Curcuminoids are major active constituents in turmeric and are associated with numerous health benefits. A combination of spectroscopic methods and chemometrics shows the suitability of turmeric for food quality control due to advantages such as speed, versatility, [...] Read more.
Turmeric consumption is continually increasing worldwide. Curcuminoids are major active constituents in turmeric and are associated with numerous health benefits. A combination of spectroscopic methods and chemometrics shows the suitability of turmeric for food quality control due to advantages such as speed, versatility, portability, and no need for sample preparation. Five calibration models to quantify curcuminoids in turmeric were proposed using benchtop and portable devices. The most remarkable results showed that Raman and NIR calibration models present an excellent performance reporting RMSEP of 0.44% w/w and 0.41% w/w, respectively. In addition, the five proposed methods (FT-IR, Raman, and NIR) were compared in terms of precision and accuracy. The results showed that benchtop and portable methods were in good agreement and that there are no significant differences between them. This study aims to foster the use of portable devices for food quality control in situ by demonstrating their suitability for the purpose. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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12 pages, 917 KiB  
Article
Measurement Strategies for the Classification of Edible Oils Using Low-Cost Miniaturised Portable NIR Instruments
by Barbara Giussani, Alix Tatiana Escalante-Quiceno, Ricard Boqué and Jordi Riu
Foods 2021, 10(11), 2856; https://0-doi-org.brum.beds.ac.uk/10.3390/foods10112856 - 18 Nov 2021
Cited by 11 | Viewed by 2371
Abstract
Miniaturised near-infrared (NIR) instruments have been increasingly used in the last few years, and they have become useful tools for many applications on different types of samples. The market already offers a wide variety of these instruments, each one having specific requirements for [...] Read more.
Miniaturised near-infrared (NIR) instruments have been increasingly used in the last few years, and they have become useful tools for many applications on different types of samples. The market already offers a wide variety of these instruments, each one having specific requirements for the correct acquisition of the instrumental signal. This paper presents the development and optimisation of different measuring strategies for two miniaturised NIR instruments in order to find the best measuring conditions for the rapid and low-cost analysis of olive oils. The developed strategies have been applied to the classification of different samples of olive oils, obtaining good results in all cases. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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13 pages, 2120 KiB  
Article
A Novel Colorimetric Nano Aptasensor for Ultrasensitive Detection of Aflatoxin B1 Based on the Exonuclease III-Assisted Signal Amplification Approach
by Yu Chen, Fuyuan Zhang, Ruobing Liu, Minxuan Liu, Yaxin Sang, Shuo Wang and Xianghong Wang
Foods 2021, 10(11), 2568; https://0-doi-org.brum.beds.ac.uk/10.3390/foods10112568 - 25 Oct 2021
Cited by 11 | Viewed by 2302
Abstract
The detection of aflatoxin B1 (AFB1) has recently garnered much attention on the issue of food safety. In this study, a novel and sensitive aptasensor towards AFB1 is proposed using an Exonuclease III (Exo III)-integrated signal amplification strategy. This reported sensing strategy is [...] Read more.
The detection of aflatoxin B1 (AFB1) has recently garnered much attention on the issue of food safety. In this study, a novel and sensitive aptasensor towards AFB1 is proposed using an Exonuclease III (Exo III)-integrated signal amplification strategy. This reported sensing strategy is regulated by aptamer-functionalized nanobeads that can target AFB1; furthermore, complementary DNA (cDNA) strands can lock the immobilized aptamer strands, preventing the signal amplification function of Exo III in the absence of AFB1. The presence of AFB1 triggers the displacement of cDNA, which will then activate the Exo III-integrated signal amplification procedure, resulting in the generation of a guanine (G)-rich sequence to form a G-4/hemin DNAzyme, which can catalyze the substrate of ABTS to produce a green color. Using this method, a practical detection limit of 0.0032 ng/mL and a dynamic range of detection from 0.0032 to 50 ng/mL were obtained. Additionally, the practical application of the established sensing method for AFB1 in complex matrices was demonstrated through recovery experiments. The recovery rate and relative standard deviations (RSD) in three kinds of cereal samples ranged from 93.83% to 111.58%, and 0.82% to 7.20%, respectively, which were comparable with or better than previously reported methods. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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Review

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22 pages, 2492 KiB  
Review
Detection of Ciguatoxins and Tetrodotoxins in Seafood with Biosensors and Other Smart Bioanalytical Systems
by Jaume Reverté, Mounira Alkassar, Jorge Diogène and Mònica Campàs
Foods 2023, 12(10), 2043; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12102043 - 18 May 2023
Cited by 3 | Viewed by 1601
Abstract
The emergence of marine toxins such as ciguatoxins (CTXs) and tetrodotoxins (TTXs) in non-endemic regions may pose a serious food safety threat and public health concern if proper control measures are not applied. This article provides an overview of the main biorecognition molecules [...] Read more.
The emergence of marine toxins such as ciguatoxins (CTXs) and tetrodotoxins (TTXs) in non-endemic regions may pose a serious food safety threat and public health concern if proper control measures are not applied. This article provides an overview of the main biorecognition molecules used for the detection of CTXs and TTXs and the different assay configurations and transduction strategies explored in the development of biosensors and other biotechnological tools for these marine toxins. The advantages and limitations of the systems based on cells, receptors, antibodies, and aptamers are described, and new challenges in marine toxin detection are identified. The validation of these smart bioanalytical systems through analysis of samples and comparison with other techniques is also rationally discussed. These tools have already been demonstrated to be useful in the detection and quantification of CTXs and TTXs, and are, therefore, highly promising for their implementation in research activities and monitoring programs. Full article
(This article belongs to the Special Issue Biosensors and Smart Analytical Systems in Food Quality and Safety: Status and Perspectives)
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